Aims & Scope
Algorithmic Finance is both a nascent field of study and a new high-quality academic research journal that seeks to bridge computer science and finance. It covers such applications as:
- High frequency and algorithmic trading
- Statistical arbitrage strategies
- Momentum and other algorithmic portfolio management
- Machine learning and other aspects of computational financial intelligence
- Agent-based finance
- Complexity and market efficiency
- Algorithmic analysis of derivatives valuation
- Behavioral finance examining the algorithms of the investors
- Applications of quantum computation to finance
- News analytics and automated textual analysis
We are seeking papers on the topics listed above, or, more generally, papers at the intersection of theoretical computer science and either theoretical or empirical finance.
Fairfield, CT, USA
Jayaram Muthuswamy †
Ken Arrow †
Cambridge, MA, USA
Boston, MA, USA
Stanford, CA, USA
Massachusetts Institute of Technology
Cambridge, MA, USA
University of Chicago
Chicago, IL, USA
Champaign, IL, USA
California Institute of Technology
Pasadena, CA, USA
New York City, NY, USA
Evanston, IL, USA
University of Maryland
College Park, MD, USA
Lawrence Berkeley National Laboratory
Washington, DC, USA
Richard J. Lipton
Georgia Institute of Technology
Atlanta, GA, USA
New Haven, CT, USA
University of Virginia
Charlottesville, VA, USA
University of Lugano
University of California
Berkeley, CA, USA
Area Editor for Machine Learning & Market Microstructure
Evanston, IL, USA
Peer Review Process and Process for Appeals
Algorithmic Finance operates a rigorous, timely, blinded peer review process (with an option for double-blind if requested) by experts in the field. Please visit our reviewer guidelines for further information about how to conduct a review.
Manuscripts submitted to Algorithmic Finance will be assessed for suitability for publication in the journal by the Editor-in-Chief. Manuscripts that are deemed unsuitable may be rejected without peer review by the Editor-in-Chief and/or the Associate Editors, and the author will be informed as soon as possible. Manuscripts that are deemed suitable for peer review are forwarded to an Associate Editor with expertise in that area who then recruits appropriate anonymous referees (a minimum of two) for confidential review. Referee reports are then assessed by the Associate Editor, who makes a decision which is then subject to approval of the Editor-in-Chief. Once approved this decision is then conveyed to the author along with the referee’s anonymized reports. The initial decision will be one of the following: rejection, acceptance without revision, or potentially acceptable after minor or major revisions.
Revised manuscripts will be appraised by the Associate Editor, who may seek the opinion of referees (prior or new) before making a decision, which again is subject to approval of the Editor-in-Chief. Once approved, this decision is then conveyed to the author along with the anonymized referee’s reports.
Once accepted, manuscripts are normally published on-line without delay and appear in the next available print issue (published quarterly). The Editor-in-Chief has ultimate responsibility for what is published in the journal. Authors may appeal decisions by contacting the Editor-in-Chief (at firstname.lastname@example.org). Authors will be informed in writing of the result of their appeal.
By default, articles published in Algorithmic Finance are available only to institutions and individuals with access rights. However, the journal offers all authors the option to purchase open access publication for their article as part of the IOS Press Open Library. This means that the final published version will be freely available to anyone worldwide, indefinitely, under a Creative Commons license and without the need to purchase access to the article. This is also referred to as “gold” open access.
Gold open access pricing
Authors who choose gold open access publication will be subject to an article publication charge of € 1500 / US$ 1500 for publication under the CC BY-NC 4.0 license or € 2150 / US$ 2150 for publication under the CC BY 4.0 license. Pricing is exclusive of possible taxes. After an article is accepted for publication, the corresponding author will be informed regarding the open access option during the production stages, and will have the opportunity to purchase open access for their article. It could be that the open access fee of an article is waived completely due an institutional agreement IOS Press has with the corresponding authors' institution. Please check the institutional agreements page for details.
Green open access
Authors who do not make use of the gold open access option may still make their article freely available using self-archiving, also referred to as green open access. Authors may make their final accepted manuscript available for free download from their personal or institutional website or institutional archive. This model is free for the author.
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Graph embedded dynamic mode decomposition for stock price prediction
William Ng, Andy Yip, Ka-Wai Siu, Albert C. Cheung, Michael K. Ng
Interest rate derivatives for the fractional Cox-Ingersoll-Ross model
Jaya P.N. Bishwal